fixed form

app.py

@@ -60,6 +60,9 @@ def write_stream_user_chat_message(user_chat, model, token, prompt):
         return new_customer_msg
 
 def get_mistral_model_tokenizer(sota_model_name):
+    max_seq_length = 2048
+    dtype = torch.float16
+    load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
     model, tokenizer = FastLanguageModel.from_pretrained(
         model_name = "unsloth/mistral-7b-instruct-v0.2-bnb-4bit",
         max_seq_length = max_seq_length,
@@ -259,15 +262,6 @@ if user_chat:
             else:
                 st.error("Please enter a customer message, or generate one for the ai to respond")
 
-# main ui prompt
-# - text box
-# - submit
-with st.form(key="my_form"):
-    prompt = st.text_area("Customer Message")
-    write_user_chat_message(user_chat, prompt)
-    if st.form_submit_button("Submit"):
-        assistant_chat.write("Hi, Human.")
-
 # below ui prompt
 # - examples
 # st.markdown("<b>Example:</b>", unsafe_allow_html=True)
@@ -289,10 +283,6 @@ if st.button("your website is straight up garbage. how do you sell high end tech
 
 # - Generate Customer Tweet
 if st.button("Generate Customer Message using Few Shots"):
-    max_seq_length = 2048
-    dtype = torch.float16
-    load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
-
     model, tokenizer = get_mistral_model_tokenizer(sota_model_name)
 
     noun_picker = DeckPicker(nouns)
@@ -318,7 +308,28 @@ st.markdown("""Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois,
     Xuechen Li, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
     - [Alpaca: A Strong, Replicable Instruction-Following Model](https://crfm.stanford.edu/2023/03/13/alpaca.html)""")
 
-if device == "cuda":
+# main ui prompt
+# - text box
+# - submit
+with st.form(key="my_form"):
+    customer_msg = st.text_area("Customer Message")
+    write_user_chat_message(user_chat, customer_msg)
+    if st.form_submit_button("Submit"):
+        st.session_state["user_msg_as_prompt"] = customer_msg
+        write_user_chat_message(user_chat, customer_msg)
+        model, tokenizer = get_model_tokenizer(sota_model_name)
+        input_text = alpaca_input_text_format.format(customer_msg)
+        st.write(f"```\n{input_text}```")
+        assistant_chat.write_stream(
+            stream_generation(
+                input_text,
+                show_prompt=False,
+                tokenizer=tokenizer,
+                model=model,
+            )
+        )
+
+if True:
     gpu_stats = torch.cuda.get_device_properties(0)
     max_memory = gpu_stats.total_memory / 1024 ** 3
     start_gpu_memory = torch.cuda.memory_reserved(0) / 1024 ** 3
@@ -327,3 +338,38 @@ if device == "cuda":
 
 st.write("Packages:")
 st.write(f"pytorch: {torch.__version__}")
+
+st.markdown("""
+## ReplyCaddy
+
+Small business owners, app developers, and freelance talent professionals need more time and money to compete for social media presence. Social media apps provide excellent reach on X, FaceBook, and Instagram, so customers sometimes request initial support from those. The correct response has always been to redirect them to the proper support funnels, such as account validation, issue classification, and prioritization.
+
+However, composing the right tone for the first response message has been challenging and time-consuming, especially when the business owner has yet to experience customer support in public. One has to match the right tone and clarity and instruct the customer to redirect to the proper support channels.
+
+By providing diverse responses, we can ensure each support message feels unique and tailored to the customer's message, avoiding the impersonal feel of a canned response.
+
+## Problems with existing solutions
+
+We prompted ChatGPT to respond an irate, emotionally charged, and informal tone to match generation criteria which we will provide below.
+
+"You are a customer support representative. compose a customer response to this tweet:
+Your website is straight up garbage. how do you sell high end technology but you cant get a website right?"
+
+[GenerationCriteria]
+
+"Thank you for reaching out and sharing your feedback. We apologize for the trouble you're experiencing with our website. Please DM us or contact our support team at [support link] so we can help resolve any issues you're encountering."
+
+First, the response is wordily composed and does not contain a request to DM; second, it has an apology and its context. Third, from our experience, ChatGPT values politeness more than a human would.
+
+As a business, we want our brands to hold a high standard for these responses.
+
+We present ReplyCaddy, an AI-powered first-response text message generator that will help us compose the right first-response message that composes personal messages and matches the customer's tone.
+
+We tested the prompt above to ReplyCaddy, and it generated these examples:
+
+"hi! let's talk about it."
+
+"we'd love to help. we're here to help!"
+
+"we understand that you are not happy with the website. please send us an email at <|url|>"
+""")